------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\abadas\Dropbox\1 - Research\98 - Coauthored Projects\2 - Millionaire Justices and Perpcetions of the Court\2 -
>  Data\Replication Files\BadasJusticeMillionaire.log
  log type:  text
 opened on:  13 Sep 2023, 11:34:54

. 
. use BadasJustusMillionaireYouGOV.dta 

. 
. ///: Summary statistics for number of Js who are millionaires. Figure 1
> graph hbar, over(J_Millionaire)

. 
. 
. /// M1 Favors wealthy. OLS. Table 1 model 1 
> reg Favors_Wealthy J_Millionaire  IdeoDistance FollowCourt ///
> CourtKnow b3.pid3 b3.ideo5 high_earner Male educ white ageg  [pweight = weight]
(sum of wgt is 933.0975979040473)

Linear regression                               Number of obs     =        939
                                                F(15, 923)        =      11.17
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1399
                                                Root MSE          =     .28751

------------------------------------------------------------------------------------
                   |               Robust
    Favors_Wealthy | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
     J_Millionaire |   .0115507   .0033064     3.49   0.000     .0050617    .0180396
      IdeoDistance |   .0607227   .0148141     4.10   0.000     .0316495    .0897958
       FollowCourt |  -.0148299   .0119246    -1.24   0.214    -.0382324    .0085726
         CourtKnow |  -.0019717   .0173916    -0.11   0.910    -.0361034    .0321601
                   |
              pid3 |
         Democrat  |    .044451   .0288174     1.54   0.123    -.0121042    .1010061
       Republican  |     .04427   .0304114     1.46   0.146    -.0154135    .1039535
                   |
             ideo5 |
     Very liberal  |   .0615513   .0502157     1.23   0.221    -.0369988    .1601014
          Liberal  |   .0317097   .0376046     0.84   0.399    -.0420908    .1055101
     Conservative  |  -.0561593   .0319922    -1.76   0.080    -.1189452    .0066266
Very conservative  |  -.1283418   .0467744    -2.74   0.006    -.2201382   -.0365453
                   |
       high_earner |  -.0247653   .0228669    -1.08   0.279    -.0696425    .0201119
              Male |   .0343078   .0212428     1.62   0.107    -.0073821    .0759976
              educ |  -.0102724   .0073433    -1.40   0.162    -.0246839    .0041392
             white |   .0074698    .023989     0.31   0.756    -.0396096    .0545491
              ageg |  -.0080485   .0063529    -1.27   0.206    -.0205162    .0044193
             _cons |   .5317685   .0460955    11.54   0.000     .4413045    .6222326
------------------------------------------------------------------------------------

. 
. 
. ///: Figure 2, panel 1 
> margins, at(J_Millionaire=(0(1)9))

Predictive margins                                         Number of obs = 939
Model VCE: Robust

Expression: Linear prediction, predict()
1._at:  J_Millionaire = 0
2._at:  J_Millionaire = 1
3._at:  J_Millionaire = 2
4._at:  J_Millionaire = 3
5._at:  J_Millionaire = 4
6._at:  J_Millionaire = 5
7._at:  J_Millionaire = 6
8._at:  J_Millionaire = 7
9._at:  J_Millionaire = 8
10._at: J_Millionaire = 9

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .5358016   .0166904    32.10   0.000     .5030461    .5685571
          2  |   .5473523   .0142078    38.52   0.000      .519469    .5752355
          3  |   .5589029    .012125    46.09   0.000     .5351071    .5826988
          4  |   .5704536   .0106788    53.42   0.000      .549496    .5914112
          5  |   .5820043   .0101451    57.37   0.000     .5620941    .6019144
          6  |    .593555   .0106618    55.67   0.000     .5726309     .614479
          7  |   .6051056   .0120949    50.03   0.000     .5813689    .6288424
          8  |   .6166563   .0141692    43.52   0.000     .5888487    .6444639
          9  |    .628207   .0166466    37.74   0.000     .5955374    .6608766
         10  |   .6397576   .0193731    33.02   0.000     .6017372    .6777781
------------------------------------------------------------------------------

. marginsplot, title(Millionaire Justices and Perceptions that Court Favors Wealthy) plot1opts(color(black)msymbol(none) lwidth(medt
> hick) ///
> xtitle(Number of Millionaire Justices) ytitle("Predicted Agreement" "Court Favors Wealthy")) ///
> recastci(rarea)  ///
> ciopts(color(gs10%85)alwidth(none)) ///
> addplot(hist J_Millionaire, fcolor(gs1%30) lwidth(none) ///
> percent ///
> yaxis(2) ///
> yscale(alt lcolor(gs10) axis(2)) ///
> ylabel(0 "0%" 15 "15%" 30 "30%" 150 " "  , /// 
> labcolor() axis(2) tlcolor(black) tlwidth(thin) labsize(small)) /// 
> ytitle(" ", axis(2)) /// 
> xlabel(0(1)9) ///
> legend(off))

Variables that uniquely identify margins: J_Millionaire

. 
. 
. 
. ///: M2 Gibson legitimacy. OLS. Table 1 model 2. 
> reg GibsonLegit J_Millionaire IdeoDistance FollowCourt ///
> CourtKnow b3.pid3 b3.ideo5 high_earner Male educ white ageg  [pweight = weight]
(sum of wgt is 941.2111882802286)

Linear regression                               Number of obs     =        945
                                                F(15, 929)        =      14.71
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2078
                                                Root MSE          =     .21328

------------------------------------------------------------------------------------
                   |               Robust
       GibsonLegit | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
     J_Millionaire |  -.0089699   .0023128    -3.88   0.000    -.0135089   -.0044309
      IdeoDistance |  -.0518486   .0119402    -4.34   0.000    -.0752815   -.0284156
       FollowCourt |    .005214   .0091368     0.57   0.568    -.0127172    .0231452
         CourtKnow |   .0184989   .0144183     1.28   0.200    -.0097974    .0467951
                   |
              pid3 |
         Democrat  |    -.04728   .0217026    -2.18   0.030    -.0898719   -.0046881
       Republican  |    .023206   .0259153     0.90   0.371    -.0276534    .0740653
                   |
             ideo5 |
     Very liberal  |   .0146084   .0406293     0.36   0.719    -.0651274    .0943443
          Liberal  |  -.0040871    .027657    -0.15   0.883    -.0583646    .0501903
     Conservative  |   .0910646   .0259371     3.51   0.000     .0401624    .1419667
Very conservative  |   .0990823   .0333014     2.98   0.003     .0337276     .164437
                   |
       high_earner |   .0458757    .018836     2.44   0.015     .0089096    .0828417
              Male |  -.0217635   .0155383    -1.40   0.162    -.0522577    .0087308
              educ |   .0098549    .006105     1.61   0.107    -.0021264    .0218362
             white |   .0391449   .0180575     2.17   0.030     .0037067     .074583
              ageg |   .0062534   .0045551     1.37   0.170     -.002686    .0151929
             _cons |   .4126416   .0342353    12.05   0.000     .3454542    .4798291
------------------------------------------------------------------------------------

. 
. ///: Figure 2, panel 2. 
> margins, at(J_Millionaire=(0(1)9))

Predictive margins                                         Number of obs = 945
Model VCE: Robust

Expression: Linear prediction, predict()
1._at:  J_Millionaire = 0
2._at:  J_Millionaire = 1
3._at:  J_Millionaire = 2
4._at:  J_Millionaire = 3
5._at:  J_Millionaire = 4
6._at:  J_Millionaire = 5
7._at:  J_Millionaire = 6
8._at:  J_Millionaire = 7
9._at:  J_Millionaire = 8
10._at: J_Millionaire = 9

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .4902623   .0125181    39.16   0.000     .4656952    .5148294
          2  |   .4812924   .0107796    44.65   0.000     .4601373    .5024476
          3  |   .4723226   .0092948    50.82   0.000     .4540814    .4905638
          4  |   .4633527   .0082028    56.49   0.000     .4472546    .4794509
          5  |   .4543829   .0076731    59.22   0.000     .4393243    .4694415
          6  |    .445413   .0078208    56.95   0.000     .4300644    .4607616
          7  |   .4364431   .0086112    50.68   0.000     .4195434    .4533429
          8  |   .4274733   .0098914    43.22   0.000     .4080612    .4468853
          9  |   .4185034   .0114989    36.40   0.000     .3959367    .4410702
         10  |   .4095336   .0133157    30.76   0.000     .3834013    .4356659
------------------------------------------------------------------------------

. marginsplot, title(Millionaire Justices and Legitimacy: Gibson Index) plot1opts(color(black)msymbol(none) lwidth(medthick) ///
> xtitle(Number of Millionaire Justices) ytitle("Predicted Legitimacy" "Gibson Index")) ///
> recastci(rarea)  ///
> ciopts(color(gs10%85)alwidth(none)) ///
> addplot(hist J_Millionaire, fcolor(gs1%30) lwidth(none) ///
> percent ///
> yaxis(2) ///
> yscale(alt lcolor(gs10) axis(2)) ///
> ylabel(0 "0%" 15 "15%" 30 "30%" 150 " "  , /// 
> labcolor() axis(2) tlcolor(black) tlwidth(thin) labsize(small)) /// 
> ytitle(" ", axis(2)) /// 
> xlabel(0(1)9) ///
> legend(off))

Variables that uniquely identify margins: J_Millionaire

. 
. 
. 
. 
. ///: M3 Applied Legitimacy. OLS. Table 1 model 3 
> reg AppliedLegit J_Millionaire IdeoDistance FollowCourt ///
> CourtKnow b3.pid3 b3.ideo5 high_earner Male educ white ageg [pweight = weight] 
(sum of wgt is 944.7275858987833)

Linear regression                               Number of obs     =        949
                                                F(15, 933)        =      23.23
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2925
                                                Root MSE          =     .21908

------------------------------------------------------------------------------------
                   |               Robust
      AppliedLegit | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
     J_Millionaire |  -.0094068   .0023615    -3.98   0.000    -.0140412   -.0047724
      IdeoDistance |  -.0585704   .0119519    -4.90   0.000    -.0820261   -.0351147
       FollowCourt |   .0201549   .0093334     2.16   0.031      .001838    .0384719
         CourtKnow |  -.0088834   .0136905    -0.65   0.517    -.0357512    .0179844
                   |
              pid3 |
         Democrat  |  -.0825006   .0218653    -3.77   0.000    -.1254115   -.0395896
       Republican  |  -.0082501   .0245944    -0.34   0.737    -.0565168    .0400167
                   |
             ideo5 |
     Very liberal  |   .0497501   .0389609     1.28   0.202    -.0267111    .1262114
          Liberal  |  -.0025225   .0269469    -0.09   0.925    -.0554061    .0503611
     Conservative  |   .1173494   .0258771     4.53   0.000     .0665653    .1681335
Very conservative  |   .2197048   .0378583     5.80   0.000     .1454074    .2940021
                   |
       high_earner |   .0817869   .0178106     4.59   0.000     .0468334    .1167403
              Male |  -.0543283   .0157076    -3.46   0.001    -.0851546    -.023502
              educ |   .0183472   .0057144     3.21   0.001     .0071327    .0295618
             white |   .0372274   .0172844     2.15   0.032     .0033066    .0711482
              ageg |   .0060301   .0046874     1.29   0.199    -.0031689    .0152291
             _cons |    .397288    .032738    12.14   0.000     .3330393    .4615368
------------------------------------------------------------------------------------

. 
. ///: Figure 3, panel 3.
> margins, at(J_Millionaire=(0(1)9)) 

Predictive margins                                         Number of obs = 949
Model VCE: Robust

Expression: Linear prediction, predict()
1._at:  J_Millionaire = 0
2._at:  J_Millionaire = 1
3._at:  J_Millionaire = 2
4._at:  J_Millionaire = 3
5._at:  J_Millionaire = 4
6._at:  J_Millionaire = 5
7._at:  J_Millionaire = 6
8._at:  J_Millionaire = 7
9._at:  J_Millionaire = 8
10._at: J_Millionaire = 9

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .4807685   .0126866    37.90   0.000     .4558709     .505666
          2  |   .4713617   .0109038    43.23   0.000     .4499629    .4927604
          3  |   .4619549   .0093802    49.25   0.000     .4435461    .4803636
          4  |   .4525481   .0082606    54.78   0.000     .4363366    .4687596
          5  |   .4431413   .0077226    57.38   0.000     .4279855    .4582971
          6  |   .4337345   .0078864    55.00   0.000     .4182575    .4492116
          7  |   .4243277   .0087122    48.70   0.000     .4072299    .4414256
          8  |   .4149209   .0100382    41.33   0.000     .3952209    .4346209
          9  |   .4055141   .0116953    34.67   0.000      .382562    .4284662
         10  |   .3961073   .0135627    29.21   0.000     .3694904    .4227243
------------------------------------------------------------------------------

. marginsplot, title(Millionaire Justices and Legitimacy: Applied Index) plot1opts(color(black)msymbol(none) lwidth(medthick) ///
> xtitle(Number of Millionaire Justices) ytitle("Predicted Legitimacy" "Gibson Index")) ///
> recastci(rarea)  ///
> ciopts(color(gs10%85)alwidth(none)) ///
> addplot(hist J_Millionaire, fcolor(gs1%30) lwidth(none) ///
> percent ///
> yaxis(2) ///
> yscale(alt lcolor(gs10) axis(2)) ///
> ylabel(0 "0%" 15 "15%" 30 "30%" 150 " "  , /// 
> labcolor() axis(2) tlcolor(black) tlwidth(thin) labsize(small)) /// 
> ytitle(" ", axis(2)) /// 
> xlabel(0(1)9) ///
> legend(off))

Variables that uniquely identify margins: J_Millionaire

. 
. 
. clear

. 
. use BadasJustusMillionaireConjoint.dta

. 
. ///: Conjoint analyses 
>    ///: These analyses require the conjoint package to be installed
> ssc install conjoint 
checking conjoint consistency and verifying not already installed...
all files already exist and are up to date.

. 
.    ///: Support for Nominee. Figure 4
>    conjoint support Net_worth J*, est(mm) h0(2.40) id(ID) graph

Estimated marginal means (MMs) 
Number of observations = 3352
Number of respondents = 672
H0 = 2.4

---------------------------------------------------------------------------------------
        Variable / Levels |     Est.        SE         t     P>|t|       LCI       UCI 
--------------------------+------------------------------------------------------------
Net worth                 |                                                            
                   25 000 |   2.3487    0.0476   -1.0766    0.2821    2.2551    2.4423 
                   50 000 |   2.4192    0.0447    0.4290    0.6680    2.3315    2.5069 
                   75 000 |   2.5000    0.0468    2.1365    0.0330    2.4081    2.5919 
                  100 000 |   2.5710    0.0516    3.3170    0.0010    2.4698    2.6723 
                  250 000 |   2.4763    0.0478    1.5976    0.1106    2.3825    2.5702 
                  425 000 |   2.4877    0.0483    1.8154    0.0699    2.3928    2.5825 
                  500 000 |   2.3914    0.0516   -0.1660    0.8682    2.2902    2.4927 
                1 000 000 |   2.2894    0.0547   -2.0233    0.0434    2.1821    2.3967 
                2 500 000 |   2.2955    0.0500   -2.0895    0.0370    2.1973    2.3937 
                5 000 000 |   2.2701    0.0538   -2.4140    0.0160    2.1644    2.3758 
--------------------------+------------------------------------------------------------
Jgender                   |                                                            
                   Female |   2.4310    0.0243    1.2781    0.2017    2.3834    2.4786 
                     Male |   2.3800    0.0234   -0.8532    0.3939    2.3341    2.4260 
--------------------------+------------------------------------------------------------
JPartisanship             |                                                            
                 Democrat |   2.5200    0.0268    4.4770    0.0000    2.4674    2.5726 
               Republican |   2.2922    0.0291   -3.7047    0.0002    2.2350    2.3493 
--------------------------+------------------------------------------------------------
JPhilosophy               |                                                            
       Case by case basis |   2.4540    0.0368    1.4679    0.1426    2.3818    2.5262 
 Living constitutionalism |   2.4318    0.0357    0.8894    0.3741    2.3616    2.5020 
              Originalism |   2.3720    0.0377   -0.7433    0.4576    2.2980    2.4460 
                Pragmatic |   2.3566    0.0369   -1.1774    0.2394    2.2842    2.4290 
               Textualist |   2.4119    0.0333    0.3563    0.7217    2.3465    2.4772 
--------------------------+------------------------------------------------------------
JRace                     |                                                            
         African American |   2.4149    0.0372    0.3990    0.6900    2.3417    2.4880 
          American Indian |   2.4963    0.0366    2.6317    0.0087    2.4244    2.5681 
                    Asian |   2.3657    0.0351   -0.9751    0.3299    2.2968    2.4347 
                 Hispanic |   2.3886    0.0371   -0.3083    0.7580    2.3157    2.4614 
                    White |   2.3668    0.0352   -0.9439    0.3456    2.2976    2.4359 
--------------------------+------------------------------------------------------------
JSchool                   |                                                            
          Duke University |   2.4034    0.0566    0.0606    0.9517    2.2922    2.5147 
       Harvard University |   2.4008    0.0567    0.0135    0.9893    2.2894    2.5121 
       Indiana University |   2.4060    0.0591    0.1013    0.9193    2.2900    2.5220 
     Princeton University |   2.4211    0.0564    0.3736    0.7088    2.3104    2.5317 
University of American ~a |   2.3487    0.0666   -0.7696    0.4418    2.2180    2.4795 
    University of Houston |   2.4578    0.0570    1.0154    0.3103    2.3460    2.5697 
   University of Michigan |   2.4357    0.0534    0.6688    0.5038    2.3309    2.5404 
 University of New Mexico |   2.3598    0.0590   -0.6806    0.4963    2.2440    2.4757 
 University of Norte Dame |   2.3655    0.0551   -0.6266    0.5312    2.2572    2.4737 
University of South Car~a |   2.3723    0.0621   -0.4459    0.6558    2.2503    2.4943 
      University of Texas |   2.4911    0.0593    1.5357    0.1251    2.3746    2.6075 
     University of Toledo |   2.3976    0.0564   -0.0427    0.9659    2.2868    2.5084 
       University of Utah |   2.3540    0.0600   -0.7675    0.4430    2.2363    2.4717 
 University of Washington |   2.4699    0.0547    1.2782    0.2016    2.3625    2.5772 
--------------------------+------------------------------------------------------------
JExperience               |                                                            
         Attorney General |   2.4375    0.0536    0.6995    0.4845    2.3322    2.5428 
    CEO of large law firm |   2.3444    0.0537   -1.0352    0.3009    2.2389    2.4499 
      Circuit Court Judge |   2.5130    0.0490    2.3050    0.0215    2.4167    2.6092 
         Corporate lawyer |   2.2862    0.0540   -2.1071    0.0355    2.1801    2.3922 
  Criminal defense lawyer |   2.4020    0.0547    0.0358    0.9714    2.2945    2.5094 
            Law professor |   2.4079    0.0521    0.1516    0.8796    2.3056    2.5102 
Member of the state leg~e |   2.3354    0.0516   -1.2511    0.2113    2.2341    2.4368 
          Patent attorney |   2.3197    0.0588   -1.3653    0.1726    2.2042    2.4352 
               Prosecutor |   2.4375    0.0503    0.7453    0.4564    2.3387    2.5363 
          Public defender |   2.4539    0.0507    1.0645    0.2875    2.3544    2.5535 
State Supreme Court Judge |   2.5072    0.0462    2.3209    0.0206    2.4165    2.5979 
--------------------------+------------------------------------------------------------
JAge                      |                                                            
                       33 |   2.3710    0.0568   -0.5101    0.6102    2.2595    2.4826 
                       35 |   2.4595    0.0520    1.1439    0.2531    2.3574    2.5615 
                       39 |   2.4000    0.0489   -0.0000    1.0000    2.3040    2.4960 
                       42 |   2.5096    0.0508    2.1566    0.0314    2.4098    2.6094 
                       45 |   2.3987    0.0516   -0.0253    0.9798    2.2974    2.4999 
                       49 |   2.4735    0.0536    1.3720    0.1705    2.3683    2.5787 
                       53 |   2.3903    0.0491   -0.1973    0.8437    2.2940    2.4867 
                       56 |   2.3725    0.0533   -0.5158    0.6062    2.2677    2.4772 
                       62 |   2.3742    0.0533   -0.4843    0.6283    2.2695    2.4789 
                       65 |   2.3810    0.0557   -0.3422    0.7323    2.2717    2.4902 
                       70 |   2.3364    0.0501   -1.2693    0.2048    2.2381    2.4348 
--------------------------+------------------------------------------------------------
JLegalYears               |                                                            
                   1 year |   2.2423    0.0494   -3.1926    0.0015    2.1453    2.3393 
                 10 years |   2.4450    0.0479    0.9396    0.3477    2.3509    2.5391 
                 12 years |   2.4809    0.0485    1.6672    0.0959    2.3856    2.5761 
                 13 years |   2.5133    0.0531    2.1325    0.0333    2.4090    2.6176 
                 15 years |   2.5028    0.0451    2.2793    0.0230    2.4142    2.5913 
                  3 years |   2.4051    0.0513    0.1000    0.9204    2.3044    2.5059 
                  5 years |   2.3969    0.0480   -0.0652    0.9480    2.3025    2.4912 
                  6 years |   2.2984    0.0458   -2.2175    0.0269    2.2085    2.3884 
                  8 years |   2.3923    0.0478   -0.1619    0.8714    2.2985    2.4860 
--------------------------+------------------------------------------------------------
JExpert                   |                                                            
 Extremely well qualified |   2.6741    0.0340    8.0587    0.0000    2.6073    2.7409 
            Not qualified |   2.1669    0.0383   -6.0873    0.0000    2.0917    2.2421 
     Not qualified at all |   2.1201    0.0372   -7.5302    0.0000    2.0471    2.1931 
                Qualified |   2.4826    0.0350    2.3588    0.0186    2.4138    2.5513 
           Well qualified |   2.5746    0.0369    4.7344    0.0000    2.5022    2.6470 
---------------------------------------------------------------------------------------

.          conjoint support Net_worth , est(mm) h0(2.40) id(ID) graph

Estimated marginal means (MMs) 
Number of observations = 3352
Number of respondents = 672
H0 = 2.4

---------------------------------------------------------------------------------------
        Variable / Levels |     Est.        SE         t     P>|t|       LCI       UCI 
--------------------------+------------------------------------------------------------
Net worth                 |                                                            
                   25 000 |   2.3487    0.0476   -1.0766    0.2821    2.2551    2.4423 
                   50 000 |   2.4192    0.0447    0.4290    0.6680    2.3315    2.5069 
                   75 000 |   2.5000    0.0468    2.1365    0.0330    2.4081    2.5919 
                  100 000 |   2.5710    0.0516    3.3170    0.0010    2.4698    2.6723 
                  250 000 |   2.4763    0.0478    1.5976    0.1106    2.3825    2.5702 
                  425 000 |   2.4877    0.0483    1.8154    0.0699    2.3928    2.5825 
                  500 000 |   2.3914    0.0516   -0.1660    0.8682    2.2902    2.4927 
                1 000 000 |   2.2894    0.0547   -2.0233    0.0434    2.1821    2.3967 
                2 500 000 |   2.2955    0.0500   -2.0895    0.0370    2.1973    2.3937 
                5 000 000 |   2.2701    0.0538   -2.4140    0.0160    2.1644    2.3758 
---------------------------------------------------------------------------------------

.    ///: Fairness of Nominee. Figure 3
>    conjoint fair Net_worth J*, est(mm) h0(2.99) id(ID) graph

Estimated marginal means (MMs) 
Number of observations = 3365
Number of respondents = 673
H0 = 2.99

---------------------------------------------------------------------------------------
        Variable / Levels |     Est.        SE         t     P>|t|       LCI       UCI 
--------------------------+------------------------------------------------------------
Net worth                 |                                                            
                   25 000 |   2.9599    0.0624   -0.4827    0.6295    2.8374    3.0824 
                   50 000 |   3.0597    0.0611    1.1410    0.2543    2.9398    3.1796 
                   75 000 |   3.0646    0.0565    1.3196    0.1874    2.9536    3.1756 
                  100 000 |   3.0822    0.0617    1.4931    0.1359    2.9610    3.2033 
                  250 000 |   3.1289    0.0639    2.1749    0.0300    3.0035    3.2544 
                  425 000 |   3.0957    0.0625    1.6911    0.0913    2.9730    3.2184 
                  500 000 |   3.0030    0.0635    0.2053    0.8374    2.8784    3.1277 
                1 000 000 |   2.8494    0.0672   -2.0919    0.0368    2.7175    2.9814 
                2 500 000 |   2.8542    0.0624   -2.1772    0.0298    2.7317    2.9767 
                5 000 000 |   2.8462    0.0678   -2.1211    0.0343    2.7130    2.9793 
--------------------------+------------------------------------------------------------
Jgender                   |                                                            
                   Female |   3.0361    0.0302    1.5261    0.1275    2.9768    3.0953 
                     Male |   2.9508    0.0300   -1.3060    0.1920    2.8918    3.0097 
--------------------------+------------------------------------------------------------
JPartisanship             |                                                            
                 Democrat |   3.1493    0.0348    4.5741    0.0000    3.0809    3.2177 
               Republican |   2.8397    0.0363   -4.1420    0.0000    2.7684    2.9109 
--------------------------+------------------------------------------------------------
JPhilosophy               |                                                            
       Case by case basis |   3.0712    0.0470    1.7275    0.0845    2.9789    3.1635 
 Living constitutionalism |   3.0405    0.0439    1.1510    0.2501    2.9543    3.1267 
              Originalism |   2.9714    0.0453   -0.4106    0.6815    2.8824    3.0604 
                Pragmatic |   2.9154    0.0447   -1.6695    0.0955    2.8276    3.0031 
               Textualist |   2.9667    0.0425   -0.5475    0.5842    2.8832    3.0502 
--------------------------+------------------------------------------------------------
JRace                     |                                                            
         African American |   3.0307    0.0452    0.9004    0.3682    2.9419    3.1195 
          American Indian |   3.1033    0.0463    2.4485    0.0146    3.0124    3.1941 
                    Asian |   2.9566    0.0439   -0.7614    0.4467    2.8704    3.0428 
                 Hispanic |   2.9503    0.0484   -0.8212    0.4118    2.8554    3.0452 
                    White |   2.9344    0.0443   -1.2558    0.2096    2.8475    3.0213 
--------------------------+------------------------------------------------------------
JSchool                   |                                                            
          Duke University |   2.9872    0.0695   -0.0406    0.9676    2.8508    3.1236 
       Harvard University |   3.0229    0.0697    0.4721    0.6370    2.8861    3.1597 
       Indiana University |   3.0213    0.0705    0.4439    0.6573    2.8829    3.1596 
     Princeton University |   3.0000    0.0725    0.1380    0.8903    2.8577    3.1423 
University of American ~a |   2.8193    0.0784   -2.1770    0.0298    2.6654    2.9733 
    University of Houston |   2.9398    0.0698   -0.7196    0.4720    2.8027    3.0769 
   University of Michigan |   3.0412    0.0654    0.7826    0.4341    2.9128    3.1695 
 University of New Mexico |   2.9587    0.0715   -0.4381    0.6614    2.8183    3.0991 
 University of Norte Dame |   3.0320    0.0707    0.5941    0.5527    2.8932    3.1708 
University of South Car~a |   3.0129    0.0767    0.2989    0.7651    2.8623    3.1635 
      University of Texas |   3.0804    0.0770    1.1736    0.2410    2.9292    3.2315 
     University of Toledo |   3.0280    0.0716    0.5306    0.5959    2.8874    3.1686 
       University of Utah |   2.9561    0.0779   -0.4345    0.6640    2.8031    3.1091 
 University of Washington |   3.0201    0.0680    0.4425    0.6582    2.8866    3.1535 
--------------------------+------------------------------------------------------------
JExperience               |                                                            
         Attorney General |   3.0484    0.0651    0.8983    0.3694    2.9207    3.1762 
    CEO of large law firm |   2.8245    0.0725   -2.2842    0.0227    2.6822    2.9668 
      Circuit Court Judge |   3.0455    0.0605    0.9173    0.3593    2.9267    3.1642 
         Corporate lawyer |   2.8656    0.0672   -1.8526    0.0644    2.7337    2.9974 
  Criminal defense lawyer |   3.0682    0.0668    1.1712    0.2419    2.9371    3.1993 
            Law professor |   3.0817    0.0616    1.4882    0.1372    2.9607    3.2027 
Member of the state leg~e |   2.9434    0.0682   -0.6829    0.4949    2.8094    3.0774 
          Patent attorney |   2.8407    0.0705   -2.1186    0.0345    2.7024    2.9791 
               Prosecutor |   2.9805    0.0643   -0.1485    0.8820    2.8543    3.1066 
          Public defender |   3.0658    0.0655    1.1578    0.2474    2.9373    3.1943 
State Supreme Court Judge |   3.1379    0.0586    2.5262    0.0118    3.0230    3.2529 
--------------------------+------------------------------------------------------------
JAge                      |                                                            
                       33 |   2.9296    0.0726   -0.8320    0.4057    2.7870    3.0722 
                       35 |   3.0034    0.0658    0.2035    0.8388    2.8743    3.1325 
                       39 |   2.9479    0.0632   -0.6670    0.5050    2.8238    3.0719 
                       42 |   3.0823    0.0660    1.3990    0.1623    2.9528    3.2118 
                       45 |   3.0686    0.0587    1.3397    0.1808    2.9534    3.1839 
                       49 |   3.0231    0.0659    0.5023    0.6156    2.8937    3.1525 
                       53 |   3.0225    0.0631    0.5150    0.6068    2.8986    3.1465 
                       56 |   2.9431    0.0666   -0.7040    0.4817    2.8125    3.0738 
                       62 |   2.9406    0.0667   -0.7410    0.4590    2.8097    3.0715 
                       65 |   2.9626    0.0694   -0.3950    0.6930    2.8263    3.0989 
                       70 |   3.0061    0.0616    0.2616    0.7937    2.8852    3.1271 
--------------------------+------------------------------------------------------------
JLegalYears               |                                                            
                   1 year |   2.8821    0.0590   -1.8301    0.0677    2.7662    2.9979 
                 10 years |   2.9661    0.0600   -0.3992    0.6899    2.8483    3.0838 
                 12 years |   3.0874    0.0604    1.6128    0.1072    2.9688    3.2060 
                 13 years |   3.1853    0.0674    2.8996    0.0039    3.0530    3.3175 
                 15 years |   3.0769    0.0555    1.5654    0.1180    2.9679    3.1860 
                  3 years |   2.9846    0.0587   -0.0918    0.9269    2.8694    3.0998 
                  5 years |   2.9455    0.0587   -0.7582    0.4486    2.8301    3.0608 
                  6 years |   2.8329    0.0600   -2.6184    0.0090    2.7151    2.9507 
                  8 years |   3.0220    0.0634    0.5040    0.6144    2.8974    3.1465 
--------------------------+------------------------------------------------------------
JExpert                   |                                                            
 Extremely well qualified |   3.2507    0.0453    5.7516    0.0000    3.1617    3.3397 
            Not qualified |   2.7759    0.0457   -4.6882    0.0000    2.6863    2.8656 
     Not qualified at all |   2.6867    0.0465   -6.5257    0.0000    2.5954    2.7779 
                Qualified |   3.0967    0.0440    2.4244    0.0156    3.0103    3.1831 
           Well qualified |   3.1490    0.0455    3.4928    0.0005    3.0596    3.2384 
---------------------------------------------------------------------------------------

.       conjoint fair Net_worth , est(mm) h0(2.99) id(ID) graph

Estimated marginal means (MMs) 
Number of observations = 3365
Number of respondents = 673
H0 = 2.99

---------------------------------------------------------------------------------------
        Variable / Levels |     Est.        SE         t     P>|t|       LCI       UCI 
--------------------------+------------------------------------------------------------
Net worth                 |                                                            
                   25 000 |   2.9599    0.0624   -0.4827    0.6295    2.8374    3.0824 
                   50 000 |   3.0597    0.0611    1.1410    0.2543    2.9398    3.1796 
                   75 000 |   3.0646    0.0565    1.3196    0.1874    2.9536    3.1756 
                  100 000 |   3.0822    0.0617    1.4931    0.1359    2.9610    3.2033 
                  250 000 |   3.1289    0.0639    2.1749    0.0300    3.0035    3.2544 
                  425 000 |   3.0957    0.0625    1.6911    0.0913    2.9730    3.2184 
                  500 000 |   3.0030    0.0635    0.2053    0.8374    2.8784    3.1277 
                1 000 000 |   2.8494    0.0672   -2.0919    0.0368    2.7175    2.9814 
                2 500 000 |   2.8542    0.0624   -2.1772    0.0298    2.7317    2.9767 
                5 000 000 |   2.8462    0.0678   -2.1211    0.0343    2.7130    2.9793 
---------------------------------------------------------------------------------------

.         
. clear 

. 
. 
. log close
      name:  <unnamed>
       log:  C:\Users\abadas\Dropbox\1 - Research\98 - Coauthored Projects\2 - Millionaire Justices and Perpcetions of the Court\2 -
>  Data\Replication Files\BadasJusticeMillionaire.log
  log type:  text
 closed on:  13 Sep 2023, 11:35:05
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